October 2013
Beginner to intermediate
364 pages
8h 8m
English
Content preview from Learning Geospatial Analysis with PythonBecome an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
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Summary
In this chapter you learned the hierarchy of geospatial analysis software including the following key elements:
- Hundreds of geospatial software packages and libraries exist
- All geospatial software can be categorized as:
- Data access
- Computational geometry
- Raster processing
- Desktop tools
- Metadata management
- Nearly all significant geospatial software is dependent on four libraries
- GDAL – raster data access
- OGR – vector data access
- PROJ.4 – geospatial data reprojection
- GEOS – computational geometry
- Raster processing software is very fragmented with many packages and frequent custom solutions
- If you come across new software trace it to the four core libraries and ask "what is the value added?"
- If you can't trace the software to one of the four core libraries ...
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I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.